CLEARML-AGENT configuration file

api {
# Notice: 'host' is the api server (default port 8008), not the web server.
api_server: http://192.168.40.210:8008
web_server: http://192.168.40.210:8080
files_server: http://192.168.40.210:8081
# Credentials are generated using the webapp, http://192.168.40:8080/profile
# Override with os environment: CLEARML_API_ACCESS_KEY / CLEARML_API_SECRET_KEY
credentials {"access_key": "XXXXXXXXXXXXXXXXXX", "secret_key": "XXXXXXXXXXXXXXXXXXXXXXXXXX"}
}

Set GIT user/pass credentials

leave blank for GIT SSH credentials

agent.git_user="user"
agent.git_pass="password"

extra_index_url: [" https://allegroai.jfrog.io/clearml/api/pypi/public/simple "]

agent.package_manager.extra_index_url= [

]

agent {
# unique name of this worker, if None, created based on hostname:process_id
# Override with os environment: CLEARML_WORKER_ID
# worker_id: "clearml-agent-machine1:gpu0"
worker_id: ""

# worker name, replaces the hostname when creating a unique name for this worker
# Override with os environment: CLEARML_WORKER_NAME
# worker_name: "clearml-agent-machine1"
worker_name: ""

# Set GIT user/pass credentials (if user/pass are set, GIT protocol will be set to https)
# leave blank for GIT SSH credentials (set force_git_ssh_protocol=true to force SSH protocol)
# git_user: ""
# git_pass: ""
# git_host: ""

# Force GIT protocol to use SSH regardless of the git url (Assumes GIT user/pass are blank)
force_git_ssh_protocol: false
# Force a specific SSH port when converting http to ssh links (the domain is kept the same)
# force_git_ssh_port: 0
# Force a specific SSH username when converting http to ssh links (the default username is 'git')
# force_git_ssh_user: git

# Set the python version to use when creating the virtual environment and launching the experiment
# Example values: "/usr/bin/python3" or "/usr/local/bin/python3.6"
# The default is the python executing the clearml_agent
python_binary: ""

# select python package manager:
# currently supported pip and conda
# poetry is used if pip selected and repository contains poetry.lock file
package_manager: {
    # supported options: pip, conda, poetry
    type: pip,

    # specify pip version to use (examples "<20", "==19.3.1", "", empty string will install the latest version)
    pip_version: "<20.2",

    # virtual environment inheres packages from system
    system_site_packages: false,

    # install with --upgrade
    force_upgrade: false,

    # additional artifact repositories to use when installing python packages
    # extra_index_url: [" https://allegroai.jfrog.io/clearmlai/api/pypi/public/simple "]

    # additional conda channels to use when installing with conda package manager
    conda_channels: ["defaults", "conda-forge", "pytorch", ]

    # If set to true, Task's "installed packages" are ignored,
    # and the repository's "requirements.txt" is used instead
    # force_repo_requirements_txt: false

    # set the priority packages to be installed before the rest of the required packages
    # priority_packages: ["cython", "numpy", "setuptools", ]

    # set the optional priority packages to be installed before the rest of the required packages,
    # In case a package installation fails, the package will be ignored,
    # and the virtual environment process will continue
    # priority_optional_packages: ["pygobject", ]

    # set the post packages to be installed after all the rest of the required packages
    # post_packages: ["horovod", ]

    # set the optional post packages to be installed after all the rest of the required packages,
    # In case a package installation fails, the package will be ignored,
    # and the virtual environment process will continue
    # post_optional_packages: []

    # set to True to support torch nightly build installation,
    # notice: torch nightly builds are ephemeral and are deleted from time to time
    torch_nightly: false,
},

# target folder for virtual environments builds, created when executing experiment
venvs_dir = ~/.clearml/venvs-builds

# cached virtual environment folder
venvs_cache: {
    # maximum number of cached venvs
    max_entries: 10
    # minimum required free space to allow for cache entry, disable by passing 0 or negative value
    free_space_threshold_gb: 2.0
    # unmark to enable virtual environment caching
    # path: ~/.clearml/venvs-cache
},

# cached git clone folder
vcs_cache: {
    enabled: true,
    path: ~/.clearml/vcs-cache
},

# use venv-update in order to accelerate python virtual environment building
# Still in beta, turned off by default
venv_update: {
    enabled: false,
},

# cached folder for specific python package download (used for pytorch package caching)
pip_download_cache {
    enabled: true,
    path: ~/.clearml/pip-download-cache
},

translate_ssh: true,
# reload configuration file every daemon execution
reload_config: false,

# pip cache folder mapped into docker, used for python package caching
docker_pip_cache = ~/.clearml/pip-cache
# apt cache folder mapped into docker, used for ubuntu package caching
docker_apt_cache = ~/.clearml/apt-cache

# optional arguments to pass to docker image
# these are local for this agent and will not be updated in the experiment's docker_cmd section
# extra_docker_arguments: ["--ipc=host", ]

# optional shell script to run in docker when started before the experiment is started
# extra_docker_shell_script: ["apt-get install -y bindfs", ]

# optional uptime configuration, make sure to use only one of 'uptime/downtime' and not both.
# If uptime is specified, agent will actively poll (and execute) tasks in the time-spans defined here.
# Outside of the specified time-spans, the agent will be idle.
# Defined using a list of items of the format: "<hours> <days>".
# hours - use values 0-23, single values would count as start hour and end at midnight.
# days - use days in abbreviated format (SUN-SAT)
# use '-' for ranges and ',' to separate singular values.
# for example, to enable the workers every Sunday and Tuesday between 17:00-20:00 set uptime to:
# uptime: ["17-20 SUN,TUE"]

# optional downtime configuration, can be used only when uptime is not used.
# If downtime is specified, agent will be idle in the time-spans defined here.
# Outside of the specified time-spans, the agent will actively poll (and execute) tasks.
# Use the same format as described above for uptime
# downtime: []

# set to true in order to force "docker pull" before running an experiment using a docker image.
# This makes sure the docker image is updated.
docker_force_pull: false

default_docker: {
    # default docker image to use when running in docker mode
    image: "nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04"

    # optional arguments to pass to docker image
    # arguments: ["--ipc=host", ]
}

# set the OS environments based on the Task's Environment section before launching the Task process.
enable_task_env: false

# set the initial bash script to execute at the startup of any docker.
# all lines will be executed regardless of their exit code.
# {python_single_digit} is translated to 'python3' or 'python2' according to requested python version
# docker_init_bash_script = [
#     "echo 'Binary::apt::APT::Keep-Downloaded-Packages \"true\";' > /etc/apt/apt.conf.d/docker-clean",
#     "chown -R root /root/.cache/pip",
#     "apt-get update",
#     "apt-get install -y git libsm6 libxext6 libxrender-dev libglib2.0-0",
#     "(which {python_single_digit} && {python_single_digit} -m pip --version) || apt-get install -y {python_single_digit}-pip",
# ]

# set the preprocessing bash script to execute at the startup of any docker.
# all lines will be executed regardless of their exit code.
# docker_preprocess_bash_script = [
#     "echo \"starting docker\"",
#]

# If False replace \r with \n and display full console output
# default is True, report a single \r line in a sequence of consecutive lines, per 5 seconds.
# suppress_carriage_return: true

# cuda versions used for solving pytorch wheel packages
# should be detected automatically. Override with os environment CUDA_VERSION / CUDNN_VERSION
# cuda_version: 10.1
# cudnn_version: 7.6

}